FIG. 1 illustrates, in a general sense, a pilot-aircraft control loop 10 having a coupling between an “objective” aircraft dynamics path 12 and a “subjective” pilot-in-the loop perception and action path 14. As shown therein, manually controlling an aircraft (including rotorcraft) involves two chains of events, connected to each other as the pilot-aircraft loop 10. First, various flight control inputs, denoted by a block 16, are received by the aircraft. Such control inputs 16 affect aircraft dynamics, denoted by a block 18. These include mechanical linkages, eventual automation features (fly-by-wire), eventual actuators and boosters and the like. The aircraft response, denoted by a block 20, denotes control surfaces that aerodynamically create the aircraft response as a function of its inertia and other factors. These elements introduce some form of delay between pilot input and aircraft response.
The pilot-aircraft loop 10 may also be represented by various items in the pilot perception and action path 14. These may be quantified by the manner in which the pilot perceives the aircraft response through a set of parallel sensory inputs. As shown in FIG. 1, such sensory inputs include a perception of visual scenery, denoted by a block 22, for observation of visible scenery through cockpit windows, a visual scanning of flight instruments block 24, a tactile perception (buffeting, stick shaker/pusher) block 26, a proprioceptive perception (vibrations, seat-of-the-pants) block 28, a vestibular perception (linear and angular accelerations) 30, and an auditory perception (air rush, caution warnings) block 32. These parallel sensory perception inputs are fused as a pilot sensory fusion block 34 to represent a pilot reaction, denoted by a block 36. Such sensory perceptions tend to have different individual neurological delays, from milliseconds for auditory cues to hundreds of millisecond for visual cues. In the will to achieve a specific task, the pilot reacts to the fusion of the different inputs to act on the flight controls, thereby “closing the loop” of the pilot-aircraft system.
“Flight simulators” are also known in the art. A Flight Simulator can include various types of Flight Simulation Training Devices (FSTD), ranging from Full Flight Simulators (FFS) that provide a six-degree-of-freedom motion bases to fixed-base Flight Training Devices (FTD), Flight Navigation Procedures Trainers (FNPT), and lower-fidelity devices. Any of those may be equipped with a dedicated vibration system which adds high-frequency, low-amplitude motions to the simulated cockpit. In general, a flight simulator may complicate the above pilot-aircraft control loop in various ways.
First, time delays are introduced to perform the simulation computations and internal communication between the components used in the flight simulator, denoted in FIG. 1 as a block 38. Such delays are known as simulator “transport delay” or “latency” depending on the measurement methods. Such delays are added to the delays discussed above, and may differ among cueing channels. For example, the transport delay may range from 30 ms for fast responding flight simulators, to 300 ms for other more conventional flight training devices. Second, because sensory cues provided in a flight simulator are simulated, they represent reality only to a certain degree of fidelity, and in some cases, they may not be provided at all. For example, the visual cues provided to the pilot may have a fixed focal distance, pilot parallax, limited field of view, limited brightness, limited contrast, limited resolution, no stereoscopic depth cues, and imperfect scene rendition. Motion cues, if provided, have limited envelope and artifacts caused by re-centering, or “washing out”, the position to account for envelope limitations.
In a typical closed-loop control system, such as a piloted aircraft, the introduction of delays decreases its stability margin. A typical example is Pilot Induced Oscillations (PIO), in which reaction delays of the pilot are identified as a factor in the aircraft becoming out of phase with the pilot's inputs. This is a significant problem that affects all kinds of aircraft, and for which detection and mitigation have been researched extensively, such as by way of example, described by L. Qingling et al., “Towards the design of a pilot-induced oscillation detection and mitigation scheme,” AIAA paper 2013-4605 (2013), the subject matter of which is incorporated herein by reference. The situation is often exacerbated in flight simulators, because of the existence of additional transport delays and the imperfect or insufficient sensory cues, even if the aircraft dynamics are perfectly modeled and simulated.
Even with high-fidelity flight dynamics and control loading models, coupled with a high-quality visual display system, a flight simulator with insufficient cues can be difficult to control even by experienced pilots. Additionally, some pilots experience “simulator sickness” as result of the modified cueing environment or PIOs. Eventually most pilots will adapt to the flight simulator with a modified control strategy, most notably with a reduction in control gain.
As applied to ab-initio helicopter flight training, a hovering maneuver is initially such a demanding and fundamental task that student pilots are rarely taught to do it in a flight simulator. Student pilots, if unchecked by the instructor, tend to over-control the cyclic, collective, and pedals to such a degree that the helicopter enters divergent oscillations which quickly end in a crash. This initial learning is generally performed in a real helicopter, thus increasing risk for student and instructor.
What is described for helicopter hovering is applicable to other flight maneuvers such as autorotation entry, autorotation descent, and autorotation landing. All of these tasks have increased risk in terms of flight training, which could be mitigated if trained in a flight simulator instead of the aircraft. Similar phenomena can be seen with respect fixed-wing aircraft. For example, one such maneuver involves correctly tracking the localizer and the glideslope during an instrument landing system approach.